Scan-o-matic: High-Resolution Microbial Phenomics at a Massive Scale
The capacity to map traits over large cohorts of individuals—phenomics—lags far behind the explosive development in genomics. For microbes, the estimation of growth is the key phenotype because of its link to fitness. We introduce an automated microbial phenomics framework that delivers accurate, pr...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Oxford University Press
2016-09-01
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| Series: | G3: Genes, Genomes, Genetics |
| Subjects: | |
| Online Access: | http://g3journal.org/lookup/doi/10.1534/g3.116.032342 |
| _version_ | 1818620028688269312 |
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| author | Martin Zackrisson Johan Hallin Lars-Göran Ottosson Peter Dahl Esteban Fernandez-Parada Erik Ländström Luciano Fernandez-Ricaud Petra Kaferle Andreas Skyman Simon Stenberg Stig Omholt Uroš Petrovič Jonas Warringer Anders Blomberg |
| author_facet | Martin Zackrisson Johan Hallin Lars-Göran Ottosson Peter Dahl Esteban Fernandez-Parada Erik Ländström Luciano Fernandez-Ricaud Petra Kaferle Andreas Skyman Simon Stenberg Stig Omholt Uroš Petrovič Jonas Warringer Anders Blomberg |
| author_sort | Martin Zackrisson |
| collection | DOAJ |
| description | The capacity to map traits over large cohorts of individuals—phenomics—lags far behind the explosive development in genomics. For microbes, the estimation of growth is the key phenotype because of its link to fitness. We introduce an automated microbial phenomics framework that delivers accurate, precise, and highly resolved growth phenotypes at an unprecedented scale. Advancements were achieved through the introduction of transmissive scanning hardware and software technology, frequent acquisition of exact colony population size measurements, extraction of population growth rates from growth curves, and removal of spatial bias by reference-surface normalization. Our prototype arrangement automatically records and analyzes close to 100,000 growth curves in parallel. We demonstrate the power of the approach by extending and nuancing the known salt-defense biology in baker’s yeast. The introduced framework represents a major advance in microbial phenomics by providing high-quality data for extensive cohorts of individuals and generating well-populated and standardized phenomics databases |
| first_indexed | 2024-12-16T17:46:52Z |
| format | Article |
| id | doaj.art-60105134da3444c786f336a3d4e9bfac |
| institution | Directory Open Access Journal |
| issn | 2160-1836 |
| language | English |
| last_indexed | 2024-12-16T17:46:52Z |
| publishDate | 2016-09-01 |
| publisher | Oxford University Press |
| record_format | Article |
| series | G3: Genes, Genomes, Genetics |
| spelling | doaj.art-60105134da3444c786f336a3d4e9bfac2022-12-21T22:22:26ZengOxford University PressG3: Genes, Genomes, Genetics2160-18362016-09-01693003301410.1534/g3.116.03234231Scan-o-matic: High-Resolution Microbial Phenomics at a Massive ScaleMartin ZackrissonJohan HallinLars-Göran OttossonPeter DahlEsteban Fernandez-ParadaErik LändströmLuciano Fernandez-RicaudPetra KaferleAndreas SkymanSimon StenbergStig OmholtUroš PetrovičJonas WarringerAnders BlombergThe capacity to map traits over large cohorts of individuals—phenomics—lags far behind the explosive development in genomics. For microbes, the estimation of growth is the key phenotype because of its link to fitness. We introduce an automated microbial phenomics framework that delivers accurate, precise, and highly resolved growth phenotypes at an unprecedented scale. Advancements were achieved through the introduction of transmissive scanning hardware and software technology, frequent acquisition of exact colony population size measurements, extraction of population growth rates from growth curves, and removal of spatial bias by reference-surface normalization. Our prototype arrangement automatically records and analyzes close to 100,000 growth curves in parallel. We demonstrate the power of the approach by extending and nuancing the known salt-defense biology in baker’s yeast. The introduced framework represents a major advance in microbial phenomics by providing high-quality data for extensive cohorts of individuals and generating well-populated and standardized phenomics databaseshttp://g3journal.org/lookup/doi/10.1534/g3.116.032342phenomicsmicrobiologygeneticshigh throughputscreening |
| spellingShingle | Martin Zackrisson Johan Hallin Lars-Göran Ottosson Peter Dahl Esteban Fernandez-Parada Erik Ländström Luciano Fernandez-Ricaud Petra Kaferle Andreas Skyman Simon Stenberg Stig Omholt Uroš Petrovič Jonas Warringer Anders Blomberg Scan-o-matic: High-Resolution Microbial Phenomics at a Massive Scale G3: Genes, Genomes, Genetics phenomics microbiology genetics high throughput screening |
| title | Scan-o-matic: High-Resolution Microbial Phenomics at a Massive Scale |
| title_full | Scan-o-matic: High-Resolution Microbial Phenomics at a Massive Scale |
| title_fullStr | Scan-o-matic: High-Resolution Microbial Phenomics at a Massive Scale |
| title_full_unstemmed | Scan-o-matic: High-Resolution Microbial Phenomics at a Massive Scale |
| title_short | Scan-o-matic: High-Resolution Microbial Phenomics at a Massive Scale |
| title_sort | scan o matic high resolution microbial phenomics at a massive scale |
| topic | phenomics microbiology genetics high throughput screening |
| url | http://g3journal.org/lookup/doi/10.1534/g3.116.032342 |
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